We propose to develop an approach for the identification of cis-regulatory sequence elements in mammalian genomes. Our approach calls for simultaneous expression profiling and TF-binding-location analysis under multiple time points and conditions relevant to a specific biological process of interest. The TF-binding regions for co-regulated genes, and their orthologous sequences in multiple mammalian species will then be analyzed in order to extract the cis-regulatory elements that mediate the co-regulation. The primary goals are to develop the computational algorithms and software that are necessary for the extraction of cis-regulatory modules based on the experimental data, and to apply this approach to the study of Sonic Hedgehog (Shh) responsive gene regulation in mouse embryonic development. The significance of this work stems from the fact that these cis-regulatory sequence elements are a key part of the """"""""control signals"""""""" in the genome that direct the temporally and spatially specific transcription of genes. By developing the general computational tools for identifying these elements, this project will contribute significantly to the understanding of the functions of the genome. This project will also generate direct knowledge on cis-elements responsive to Shh signaling, which is fundamental in numerous processes in developmental and cancer biology.
Our specific aims are: 1) Development of statistical methods and computational algorithms for identifying cis-regulatory modules. 2) Development of a software application to support studies of gene regulation from combined expression profiling and TF-binding location data. 3) Identification of cis-regulatory elements controlling Shh- responsive transcriptional events in selected developmental processes in mouse using the proposed approach. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG003903-02
Application #
7287443
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Good, Peter J
Project Start
2006-09-19
Project End
2009-07-31
Budget Start
2007-08-01
Budget End
2008-07-31
Support Year
2
Fiscal Year
2007
Total Cost
$682,740
Indirect Cost
Name
Stanford University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Peterson, Kevin A; Nishi, Yuichi; Ma, Wenxiu et al. (2012) Neural-specific Sox2 input and differential Gli-binding affinity provide context and positional information in Shh-directed neural patterning. Genes Dev 26:2802-16
Park, Joo-Seop; Ma, Wenxiu; O'Brien, Lori L et al. (2012) Six2 and Wnt regulate self-renewal and commitment of nephron progenitors through shared gene regulatory networks. Dev Cell 23:637-51
Ma, Wenxiu; Wong, Wing Hung (2011) The analysis of ChIP-Seq data. Methods Enzymol 497:51-73
Yang, Hong; Chen, Xi; Wong, Wing Hung (2011) Completely phased genome sequencing through chromosome sorting. Proc Natl Acad Sci U S A 108:12-7
Li, Jun; Jiang, Hui; Wong, Wing Hung (2010) Modeling non-uniformity in short-read rates in RNA-Seq data. Genome Biol 11:R50
Niakan, Kathy K; Ji, Hongkai; Maehr, Rene et al. (2010) Sox17 promotes differentiation in mouse embryonic stem cells by directly regulating extraembryonic gene expression and indirectly antagonizing self-renewal. Genes Dev 24:312-26
Lee, Eunice Y; Ji, Hongkai; Ouyang, Zhengqing et al. (2010) Hedgehog pathway-regulated gene networks in cerebellum development and tumorigenesis. Proc Natl Acad Sci U S A 107:9736-41
Jiang, Hui; Wong, Wing Hung (2009) Statistical inferences for isoform expression in RNA-Seq. Bioinformatics 25:1026-32
Ouyang, Zhengqing; Zhou, Qing; Wong, Wing Hung (2009) ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells. Proc Natl Acad Sci U S A 106:21521-6
Nishi, Yuichi; Ji, Hongkai; Wong, Wing H et al. (2009) Modeling the spatio-temporal network that drives patterning in the vertebrate central nervous system. Biochim Biophys Acta 1789:299-305

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